↓ 1 callersFunctioncalculate_fps(img, pTime, pos=(50, 80), color=(0, 255, 0), scale=4, thickness=4)
computer-vision/04_pose.py:6
↓ 1 callersFunctioncalculate_fps(img, pTime, pos=(50, 80), color=(0, 255, 0), scale=4, thickness=4)
computer-vision/03_face_mesh.py:6
↓ 1 callersFunctioncalculate_fps(img, pTime, pos=(50, 80), color=(0, 255, 0), scale=4, thickness=4)
computer-vision/01_code_base_video_capture.py:5
↓ 1 callersFunctioncalculate_fps(img, pTime, pos=(50, 80), color=(0, 255, 0), scale=4, thickness=4)
computer-vision/02_hands.py:6
↓ 1 callersFunctioncalculate_fps(img, pTime, pos=(50, 80), color=(0, 255, 0), scale=4, thickness=4)
computer-vision/05_holistic.py:6
↓ 1 callersFunctioncompute_bbox_mask_targets_and_label given rois, overlaps, gt labels, seg, compute bounding box mask targets :param rois: roidb[i]['boxes'] k * 4 :param overlaps: roidb[i]['m
serving-ml-models/backend/detection/RetinaFace/rcnn/processing/bbox_regression.py:184
↓ 1 callersFunctioncompute_bbox_mask_targets_and_label given rois, overlaps, gt labels, seg, compute bounding box mask targets :param rois: roidb[i]['boxes'] k * 4 :param overlaps: roidb[i]['m
serving-ml-models/backend/detection/RetinaFaceAntiCov/rcnn/processing/bbox_regression.py:184
↓ 1 callersMethodcreate_roidb_from_box_list given ground truth, prepare roidb :param box_list: [image_index] ndarray of [box_index][x1, x2, y1, y2] :param gt_roidb: [ima
serving-ml-models/backend/detection/RetinaFaceAntiCov/rcnn/dataset/imdb.py:109